Laura Matzen, Michelle A Leger, Geoffrey Reedy (Sandia National Laboratories)

Binary reverse engineers combine automated and manual techniques to answer questions about software. However, when evaluating automated analysis results, they rarely have additional information to help them contextualize these results in the binary. We expect that humans could more readily understand the binary program and these analysis results if they had access to information usually kept internal to the analysis, like value-set analysis (VSA) information. However, these automated analyses often give up precision for scalability, and imprecise information might hinder human decision making.

To assess how precision of VSA information affects human analysts, we designed a human study in which reverse engineers answered short information flow problems, determining whether code snippets would print sensitive information. We hypothesized that precise VSA information would help our participants analyze code faster and more accurately, and that imprecise VSA information would lead to slower, less accurate performance than no VSA information. We presented hand-crafted code snippets with precise, imprecise, or no VSA information in a blocked design, recording participants’ eye movements, response times, and accuracy while they analyzed the snippets. Our data showed that precise VSA information changed participants’ problem-solving strategies and supported faster, more accurate analyses. However, surprisingly, imprecise VSA information also led to increased accuracy relative to no VSA information, likely due to the extra time participants spent working through the code.

View More Papers

cozy: Comparative Symbolic Execution for Binary Programs

Caleb Helbling, Graham Leach-Krouse, Sam Lasser, Greg Sullivan (Draper)

Read More

Demo #4: Attacking Tesla Model X’s Autopilot Using Compromised...

Ben Nassi (Ben-Gurion University of the Negev), Yisroel Mirsky (Ben-Gurion University of the Negev, Georgia Tech), Dudi Nassi, Raz Ben Netanel (Ben-Gurion University of the Negev), Oleg Drokin (Independent Researcher), and Yuval Elovici (Ben-Gurion University of the Negev) Best Demo Award Winner ($300 cash prize)!

Read More

Deceptive Deletions for Protecting Withdrawn Posts on Social Media...

Mohsen Minaei (Visa Research), S Chandra Mouli (Purdue University), Mainack Mondal (IIT Kharagpur), Bruno Ribeiro (Purdue University), Aniket Kate (Purdue University)

Read More

UIScope: Accurate, Instrumentation-free, and Visible Attack Investigation for GUI...

Runqing Yang (Zhejiang University), Shiqing Ma (Rutgers University), Haitao Xu (Arizona State University), Xiangyu Zhang (Purdue University), Yan Chen (Northwestern University)

Read More